GenomicPlot
Bioc currentPlot profiles of next generation sequencing data in genomic features
Release Lineage
Entered 3.18 · Oct 25, 2023
Current · Requires R 4.6
Description
Visualization of next generation sequencing (NGS) data is essential for interpreting high-throughput genomics experiment results. 'GenomicPlot' facilitates plotting of NGS data in various formats (bam, bed, wig and bigwig); both coverage and enrichment over input can be computed and displayed with respect to genomic features (such as UTR, CDS, enhancer), and user defined genomic loci or regions. Statistical tests on signal intensity within user defined regions of interest can be performed and represented as boxplots or bar graphs. Parallel processing is used to speed up computation on multicore platforms. In addition to genomic plots which is suitable for displaying of coverage of genomic DNA (such as ChIPseq data), metagenomic (without introns) plots can also be made for RNAseq or CLIPseq data as well.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
62 57 exported
Complexity
12.2 avg / 101 max
Call network
62 nodes / 113 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
14,278
Files
126
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
57
Internal functions
5
Testing & CI
Has tests
Yes
Test-to-code ratio
0.07
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
50%
Unsafe pattern score
0
Dep constraint coverage
32.4%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.4.0
System requirements
–
C++ standard
–
License
GPL-2
License flags
SPDX valid, OSI approved
History
Versions
6
First release
2024-04-08
Latest release
2026-04-28
Avg cadence
141 days
Cold removal rate
–
Dep drift
4
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 98%
- Return-value docs
- 100%
- References docs
- 0%
Datasets
| Name | Class | Rows × Cols | Also in |
|---|---|---|---|
| gencode.v19.annotation_chr19.gtf.granges | – | – | – |
| gf5_genomic | list | – | No other package |
| gf5_meta | list | – | No other package |
| test_file1 | data.frame | 25 × 4 | No other package |
| test_file2 | data.frame | 25 × 3 | No other package |
| test_file3 | data.frame | 17 × 2 | No other package |
| test_file4 | data.frame | 17 × 1 | No other package |
Topics
People
- Shuye Pu author maintainer
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("GenomicPlot")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.